The following description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
Consumers continue to experience an increasingly blurred distinction between real-world and on-line interactions. With the advent of object recognition technologies available today, consumers can now virtually interact with real-world objects through their smart phones. For example, consumers can capture an image of a movie poster via their cell phones. In response, the cell phone can construct an augmented reality interaction or game overlaid on the display of the cell phone. In fact, the Applicant has pioneered such technologies through their iD® technologies as implemented by DreamPlay™ (see URL www.polygon.com/2013/1/9/3851974/disney-dreamplay-ar-app-disney-infinity). Other technologies that attempt to offer similar experiences include the following:                Layar® (see URL www.layar.com),        Qualcomm Vuforia™ (see URL www.qualcomm.com/solutions/augmented-reality)        BlippAR.com™ (see URL www.blippar.com), and        13th Lab (see URL www.13thlab.com).        
Unfortunately, such technologies are limited in scope and typically are only capable of recognizing a single object at a time (e.g., a single toy, a single person, a single graphic image, etc.). In addition, a consumer must position their cell phone into a correct position or orientation with respect to the object of interest, then wait for their cell phone to analyze the image information before engaging content is retrieved. Ideally a consumer should be able to engage content associated with an object of interest very quickly and should be able to engage many objects at the same time. The above referenced companies fail to provide such features.
Other efforts have been made in the field of object recognition. For example, in the publication “Silhouette-Based Object Phenotype Recognition Using 3D Shape Priors” by Chen et al., published in the 2011 IEEE International Conference on Computer Vision, Nov. 6-13, 2011, Chen states that there is a fundamental problem in recognizing three-dimensional (3D) objects from one or more two-dimensional (2D) views in computer vision. However, Chen takes a computationally intensive approach of generating large numbers of possible poses. Unfortunately, such implementations are not suitable for mobile handheld devices and merely attempt to view shape as an identifier. Chen points out numerous deficiencies with respect to recognizing 3D objects.
U.S. Pat. No. 6,858,826 “Method and Apparatus for Scanning Three-Dimensional Objects” issued to Mueller et al., filed Aug. 13, 2002, also recognizes the difficulty of recognizing 3D objects. Mueller specifically points out the difficulty of prior techniques that scan for 2D color information and separately scan for 3D information. Mueller rather uses a series of 2D color images to derive 3D points in space. However, such an approach fails to provide scale invariance when conducting recognition in handheld devices.
U.S. Pat. No. 6,954,212 “Three-Dimensional Computer Modeling” issued to Lyons et al., filed Nov. 5, 2002, describes building a 3D computer model of an object by aligning image data with silhouettes of computer generated model. Although Lyon discloses adequate building of 3D models, such modeling information is not practical for full 3D object recognition or tracking on resource-constrained devices.
U.S. Pat. No. 7,728,848 “Tools for 3D Mesh and Texture Manipulation” issued to Petrov et al., filed Mar. 28, 2001, teaches a method for editing three-dimensional computer models and textures that provides more precisely selected portions of the model for editing, allowing textures to be moved more easily on the model and allowing better blending of the appearance of adjacent textures.
U.S. Patent Publication 2006/0232583 “System and Method of Three-Dimensional Image Capture and Modeling” to Petrov et al., filed May 30, 2006, teaches a system for constructing a 3D model of an object based on a series of silhouette and texture map images.
U.S. Patent Publication 2011/0007072 “Systems and Methods for Three-Dimensionally Modeling Moving Objects” to Khan et al., filed Jul. 9, 2009, describes building a 3D model by first capturing images of an object from different viewpoints, identifying silhouettes of the object in each viewpoint, and then identifying the silhouette boundary pixels.
U.S. Patent Publication 2013/0188042 “System and Method for Object Measurement” to Brooksby, filed Mar. 12, 2013, describes building a model of an object by combining 2D images with a 3D CAD model. The objects are built by linking images with point correspondences from model parameters.
U.S. Patent Publication 2008/0143724 “Method and Apparatus for Probabilistic Atlas Based on Shape Modeling Technique” to Russakoff, filed Dec. 19, 2006, describes generating shape models of breasts based on silhouettes. Control points are placed along the edges of a two-dimensional breast silhouette and are used for deformational image analysis during mammogram viewing by comparing the control points placed on a baseline breast silhouette and the control points placed on an updated breast silhouette.
However, none of the references mentioned above provides an accurate 3D object recognition technique that is not computationally intensive, allowing real-time tracking of recognized objects. Thus, there is still a need to improve upon conventional 3D object recognition techniques.
All publications herein are incorporated by reference to the same extent as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.